Research on Security Protection Strategies for Big Data Platforms under Cloud Computing Architecture

Abstract

The widespread adoption of cloud computing architectures brings advantages to big data platforms, such as high-concurrency
processing, elastic scalability, and resource sharing. However, it also presents security risks characterized by cross-domain, dynamic, and
systematic traits. Based on the security challenges in cloud computing environments, this study analyzes the core risks arising from multitenant isolation, enhanced data mobility, and elastic resource scheduling, and constructs a cloud security protection framework encompassing zero-trust access control, cloud-edge-terminal encryption systems, automated configuration management, and continuous monitoring.
On this basis, three optimization paths are proposed: intelligent threat detection, visual compliance governance, and joint protection mechanisms between cloud service providers and enterprises, aiming to enhance the platform's proactive defense capabilities and collaborative
governance effectiveness. The study seeks to provide scalable technical ideas and practical references for building security systems in
cloud-based big data platforms.